基因芯片数据分析

Data analysis in microarray experiment

基因芯片是近年发展起来的自动化的、高通量的研究生物学问题的一门新技术。它综合了多学科的成就,在大规模研究基因功能的领域中已经有了卓有成效的应用。对大量产生的数据如何有效地分析,成为芯片研究中的一个热点。总体上,数据分析方法可分为非指导的方法和指导的方法。在分析前需要对数据进行标准化和精简,对分析结果需要检验和进行生物学分析。作者对目前常用的一些统计学方法作一介绍,并讨论其适用范围及优缺点。

Genechip, representing the integration of multiple scientific field progress, is a newly developing hightechnology used to solve biology puzzle with automated and high-flux features. It has a successful application inlarge-scale research in genes function. After a relative long developing period, the method how to efficientlyanalyse mass data generated by chip experiment has become a hotspot in the chip research community. In principal,the method can be divided into two categories, the unsupervised method and the supervised method. Besides dataanalysis itself, two procedures performing before and after the analysis need to be paid attention to: the former isdata normalization and reduction, the later is statistical test and biologic verification. Many commonly used statis-tical approaches and their merits and demerits will be introduced.